A five-year NIDA Scientist Development Award (K01) is requested to support training and research intended to integrate the candidate's previous training in substance abuse and psychiatric epidemiology with the latest methods in genetic epidemiology, psychiatric genetics and molecular genetics. In the long term, the candidate wishes to combine epidemiological and genetic methods in the analysis of the interaction of biological and social factors in the development of risk to psychoactive substance use disorders. Formal training will be provided by courses and seminars in behavioral and psychiatric genetics, molecular genetics, behavioral pharmacology, quantitative and statistical genetics. Further training will be provided by weekly meetings with the candidate's mentors, Drs. Lindon Eaves and Kenneth Kendler, supported by other colleagues at the Virginia Institute for Psychiatric and Behavioral Genetics. In addition he will attend the International Twin Methodology Workshop, the short course in Medical and Experimental Mammalian Genetics (Jackson Laboratory) and the New England Biolabs Molecular Biology and PCR Summer Workshop. The candidate's research is intended to answer a series of questions about genetic and social influences on environmental and behavioral risk factors for substance use through analysis of existing data, and the collection of new data, from the families of adolescent twins ascertained through the population-based North Carolina and Virginia School Age Twin Registries. The Virginia sample has already been assessed longitudinally on an extensive protocol of face-to-face home interview with twins and parents. Part of the North Carolina sample has also been studied by mailed questionnaire. During the proposed project a second wave of data will be collected in North Carolina and the same instrument will be used with the Virginia sample to provide validation data. Altogether c. 3,200 families of twins aged 6-18 will be studied. A variety of standard statistical methods and multivariate structural modeling techniques will be used to estimate the contributions of genetic and non-genetic factors to the individual risk factors, their interrelationships, and their developmental trajectories.